The CEO's 2026 AI Exam: Can These 5 Plays Deliver?

I recently read IBM's 2026 CEO study (co-produced with Oxford Economics), and I froze on the very first number. I forwarded it to a friend who runs a company:

"Look at this: 76% of CEOs say their company already has a Chief AI Officer (CAIO). Just last year, that figure was 26%."

He replied: "Three times in a year? That's insane."

This isn't about tripling. This is a wholesale restructure. AI isn't knocking at the door anymore — it has walked straight into the boardroom.

Let me lay the cards on the table. There's a set of figures in the study that genuinely sting:

• 69% of CEOs say AI is already rewriting their most core business — the parts that would sink the company if the money stopped flowing.
• 77% of CEOs say the people who run technology and the people who run talent are converging.
• The share of CEOs with a Chief AI Officer jumped from 26% to 76% in a single year.

Each one alone is alarming. Taken together, the message is clear: this is the trend.

A CEO sees the trend — and then what? Shout slogans? That doesn't work. The study offers five concrete plays. Let me unpack them for you one by one.

Play 1: Reshuffle the seats at the C-suite

What does "reshuffling the seats" mean? Re-examining who in the company calls the shots, who has the final say, and whose job AI is turning over.

Every CEO knows they need to transform. What actually separates the front-runners is how steadily they execute: whether they can grit their teeth and hold on until the change lands.

The study found that CEOs who reconfigured their leadership through an AI-first mindset roll out AI projects across the company 10% more than everyone else.

What, exactly, gets rearranged? Three things.

First, the delegation has to be thought through: which powers go to which level — and above all, put real, money-in-hand authority into the hands of COOs and frontline business leaders, not just surface-level backing.

Second, give the CAIO real authority, not just a title, so they can genuinely direct the company-wide transformation.

Third, create new roles at every level to absorb AI, so no one is left empty-handed.

Here's one more number, and it's key: 85% of CEOs believe every business leader should become a technical expert in their own domain.

What does that mean? The age-old line between "the people who run the business" and "the people who know the technology" has collapsed. From now on, every leader has to touch technology at least a little.

There's a line in the study that I love: "Speed, in fact, comes from 'productive friction'; it's not that fewer conflicts make things faster."

In other words, it is precisely the uncomfortable mutual challenge and back-and-forth cross-checking that makes a company fast. Don't fear the fight; fear nobody daring to slam the table.

I've seen too many companies blow up their "coordination meetings" the moment they go on AI. That is exactly backwards.

Play 2: Get the AI flywheel spinning

What do we mean by a "flywheel"? You push the first revolution with all your might, drained. But once it turns, it spins itself faster and faster — and pulls other people in along the way.

The most aggressive CEOs live off exactly this rotation: their company-wide AI deployments run 23% ahead of everyone else's.

Now, of the routine decisions on your plate today, how many could AI make directly, without a human in the loop?

The answer is 25%. By 2030, the CEOs' own expectation is that this figure climbs all the way to nearly 48% — close to a doubling.

Oh. So people aren't useful anymore, then?

No. The human's job has just moved.

In the past, people were the deciders. Going forward, people are the ones who write the rules — who design the algorithmic logic behind those decisions and set the guardrails, only stepping in for the two conditions: an exception, or something that touches real money or ethics.

Think about it — it's counterintuitive: the fewer decisions you personally make, the more you're worth. Because what you're building is no longer a single call, but a "decision engine" that keeps producing the right ones.

That's why the research line — "What limits us is never the technology. It's ourselves." — lands.

Play 3: Customize your AI mix, don't just pick a model

This move, the numbers sting the hardest:

• Nearly 80% of CEOs expect AI to bring the company a big pile of money by 2030.
• But only 24% know where that money is going to come from.

See the pattern? The vast majority smells the roast — but has no idea where the meat is.

Meanwhile, the CEOs who fold their own data and IP into proprietary AI models and bespoke agents expect 13% of their 2030 revenue to come from "products we haven't shipped yet."

So what is the "right" AI mix? It's not dragging one big model home and calling it done. It's a blend:

• A large language model (LLM) to handle "working through the reasoning";
• A small language model (SLM) to handle "fast and accurate";
• A specialized model (ULM) to chew on a single narrow task.

Each layer is fine-tuned on your own data. Your IP is the layer no one else can buy.

Behind this approach sits an obsession called "AI sovereignty": 83% of CEOs say keeping that sovereignty is critical.

Why? Anyone can buy the same model from scratch. But whatever can be bought is not a moat. The moat is the layer of your company that no competitor can replicate.

The best AI is the one-of-a-kind AI. It's "your own."

Play 4: Put human intelligence and AI intelligence at the wheel together

What does "orchestration" mean? Not shoving AI into your existing way of working, but re-designing how humans and machines split the work: who does what, who has the final say.

Today, AI gives humans a hand. By 2030, people give AI a hand — correcting its direction, feeding it common sense, feeding it strategy.

The research shows that CEOs who proactively reshuffle how their teams work together are more than twice as likely to get the business done — and done well.

How do you divide the labor? Hand AI the specialized tasks it knocks out fast and accurately. Free up human brains to spot patterns across departments, to ask the questions AI never thought to ask, and to reconnect the machines' output to the strategic throughline.

And there's that same 77% again: 77% of CEOs believe the old line between "business" and "technology" has grown outdated. Since the two can't be pulled apart, just tear the wall down.

There's also an analogy from the research I keep replaying:

"Each department turning alone is steady progress; all departments woven into one network, the progress is exponential."

Going it alone is climbing the stairs; weaving into a single web is riding the elevator.

Play 5: Reserve a seat for the unpredictable

The last play — and the easiest to laugh at — is quantum.

You may think quantum is ten thousand miles away from you. But the research is blunt: the "lane-change" that quantum brings will arrive sooner than you think. From "quantum advantage arrives" to "quantum disrupts an industry", the window is very short.

So what are the leaders who have already moved actually doing?

• 82% of AI-first CEOs are already partnering with players in the quantum ecosystem — banding together to complement one another, share the risk, and accelerate learning. Among all CEOs, that figure is only 50%.
• On the flip side, only 46% of CEOs have a dedicated team hunting for "where quantum can be applied, and where its value lies."

On one side, 82% have already gone all-in together; on the other, 46% haven't even scouted the lay of the land.

That gap is exactly the window into what comes next.

No one can eat the quantum meal alone. The infrastructure and the specialist skill are too expensive, too specialized; a single company just can't carry the load.

This isn't free-riding, either. Look back: these moves — openness, interoperability, trust — are precisely what makes you the winner today in the AI era. Underneath, it's the same logic, just on a different vehicle.

Back to one line

After these five plays, my biggest takeaway is this: Most of these, really, are about the boss themselves, about culture, about organization. About the technology itself — very little.

This may be the passage that stings me the most in the entire study:

"Mindset is as important as technology — sometimes even more important."

Technology can be bought. But what can be bought is never a moat.

How you set the direction, how you hand over power, how you organize people into one team, how you walk through the friction fight by fight — no one can do any of it for you.

The 2026 exam paper is already clearly on the table.

Whether you sit for it is entirely up to you.